Computers
are killing the U.S. energy economy. Our silicon addiction is causing the national grid system
to OD. At one point during the seemingly never ending California energy crisis,
one of the national evening news programs contrasted the power requirements of a small one-story
server farm with a 60-story office building. The diminutive server farm needed as much juice
as the huge skyscraper.

The huge power
supply drain at server farms is
a natural consequence of the second law of thermodynamics, which in one form
states that irreversible processes create entropy (which can be loosely stated
as heat). AND gates, one of the most fundamental logic elements within a microprocessor,
are presently designed to work in only one direction, and are thus irreversible
in their operation. So whenever an AND gate clears (destroys) one bit of data,
it also generates heat. The more AND gates, the more heat. Obviously, this is
incredibly wasteful of energy resources. As Professor Tomasso Toffolli of M.I.T.
put it, "How much free energy do you have to lose for a computation?"

Consequently,
as you build ever faster and denser silicon-based processors that are irreversible
in operation, heat dissipation, i.e., power consumption, eventually becomes
an enormous obstacle. The short stack server farms discussed in that news story
are thus consuming much more energy than gigantic office buildings because of
their incredible wastefulness. The power crisis happened first in Silicon Valley
because it is ground zero for probably the highest concentration of server farms
and bit burning AND gates in the world. Entropy is killing them  and Californias
lights. The rest of the global silicon economy is assuredly next.

Today (2001), the best
commercial fabrication techniques produce devices with a line width of about
0.13 to 0.15 micron. But semiconductors will assuredly get faster and Internet
server farms will get much more powerful and their demands for energy due to
their extraordinary wastefulness will become increasingly insatiable, even if
they were all to use low power versions of silicon. By about 2010, or just about
the time it will take for building all those new generator plants and getting
the half-baked Alaska oil flowing (if), the power requirements of Moores
law-driven "classic" computing systems will have become truly enormous,
making all these new power resources feebly redundant.

But quantum computers
and communications dont have an entropy problem, at least in the classic
sense. First, quantum computations happen all at once  there is no sequential
step by wasteful step process as in a classic semiconductor computer. But second,
and much more critical, quantum computers by definition are inherently reversible
because the laws of quantum mechanics are themselves reversible.

If a classic,
i.e., non-quantum, computation could be reversed (unwound back to its original
state), then no heat would be lost because the second law of thermodynamics
would not be involved. The radical notion of reversible computer logic was discovered
independently by Dr. Charles Bennett of IBM, and later by Dr. Edward Fredkin
of M.I.T. Dr. Fredkin and Dr. Toffolli have since proved that a classic computer
using reversible "Fredkin" logic could do anything that a conventional,
irreversible system can. But just as it is cheaper to manufacture large displacement,
fuel inefficient car engines than smaller ones with expensive turbochargers,
so too, "It is cheaper to build systems that waste energy, as opposed to systems
that conserve it" says Toffolli. The natural tendency for semiconductor companies,
therefore, has been to design and build wasteful (i.e., irreversible) systems.
On the other hand, sufficiently small systems, including quantum systems, are
naturally reversible.

In nature, reversibility
is a key factor in any type of truly successful, dynamic organism. As Henry
Baker (of the former Thimble Systems in Encino, CA) stated it, "Biological computational
processes, so unlike silicon ICs, rely on reversible chemical reactions, and
are not so nearly wasteful of energy." Baker gives the example of DNA replication,
which, he says, "if it wasted as much heat per bit as a modern CPU, would cause
a developing chick to fry inside its own egg!" This is not to say that quantum
computers dont require energy just because they are reversible. They will
need juice to run, but only as a means to a very minimal power requirement end.

Quantum computing
and communications completely turn upside down our notions of time and space.
What may be an impossible problem to solve on the worlds largest supercomputer
could take an instant on a tiny quantum machine. For example, quantum-based,
factorizing code breakers are often cited as a prime use of such machines. Todays
digital supercomputers would take billions of years to find the prime factors
of a number that is a few hundred digits long, whereas large-scale quantum computers
might perform that task in just seconds.

Inversely, secure
quantum cryptographic signals are now routinely sent over fiber-optic cables
and through the air for tens of miles. When secure quantum information is exchanged,
cryptographic protocols use the laws of fundamental physics to ensure privacy.
This is in marked contrast to current public-key crypto systems that decrypt
a message requiring a time-consuming classic computation, such as prime factorization.
Many, if not most, public key systems will likely become obsolete overnight
when quantum computers become generally available.

Thus, for a very
wide variety of reasons, quantum based systems are THE business technology story
of the new millennium. Quantum computing and communications are a huge paradigm
shift that is going to cause massive disruptions in numerous social, economic
and industrial areas. They also usher in an era in which it is completely accepted
that information processing and physics are fully interchangeable. IBM, the
NSA, Siemens, DARPA NIST, the NSF, and other major commercial, governmental
and academic organizations worldwide have now recognized and embraced the great
commercial and technological significance of quantum information science. IBMs
quantum R&D effort is quite advanced. The following description of quantum computing from IBM is also among the
best available. [Some further explanatory comments have also been added]:

"Quantum
computers get their power by taking advantage of certain quantum physics properties
of atoms or nuclei that allow them to work together as quantum bits, or "qubits,"
to be the computer's processor and memory. A quantum particle, such as an electron
or atomic nucleus, can exist in two states at the same time -- say, with its
spin simultaneously in the up and down states. This constitutes a qubit. When
the spin is up, the atom can be read as a 1, and the spin down can be read as
a 0. This corresponds with the digital 1s and 0s that make up the language of
traditional computers. The spin of an atom up or down is the same as turning
a transistor on and off, both represent data in terms of 1s and 0s. Qubits differ
from traditional digital computer bits, however, because an atom or nucleus
can be in a state of "superposition," representing simultaneously both 0 and
1 and everything in between."

"Moreover,
without interference from the external environment, the spins can be "entangled"
in such a way that effectively wires together a quantum computer's qubits. Two
entangled atoms act in concert with each other -- when one is in the up position,
the other is guaranteed to be in the down position. Entanglement makes possible
highly orchestrated predictability and you can apply logical operations to entangled
superpositions ." [Entanglement is a subtle quantum kind of correlation
having no classical equivalent, and can be roughly described by saying that
two systems are entangled when their joint state is more definite and less random
than the state of either system by itself.]

" The
combination of superposition and entanglement permit a quantum computer to have
enormous power, allowing it to perform calculations in a massively parallel,
non-linear manner exponentially faster than a conventional computer. For certain
types of calculations -- such as complex algorithms for cryptography or searching
-- a quantum computer can perform billions of calculations in a single step.
So, instead of solving the problem by adding all the numbers in order, a quantum
computer would add all the numbers simultaneously."

Fig.1
When information is represented as a quantum state rather than in terms of classical
bits, quantum information science is described as being generalizations or extensions
of classical theory. The well-established theory of classical information and
computation is thus a subset of a much larger topic, the emerging theory of
quantum information and computation. (source, NSF)

At
the angstrom scale of electron motion, as long as its motion is unobserved it
is assumed to be "wavelike"; it can take all possible trajectories.
But once observed, the wave collapses (called "decoherence") and becomes
particle-like. Or stated more properly by David DiVincenzo of IBMs T.J.
Watson Research Center, "An unobserved attribute of a system can be in
a superposition of different values, while an observed attribute assumes a definite
value." In other words, as long as you dont "look" at the
quantum system, its continually calculating a huge probability of outcomes
at the same time. In fact, a single qubit, because of the tremendous power of
superposition, is in of itself a parallel computer. But when you interfere with
it in any way, the system collapses ("decoheres") into a single state,
destroying all other possibilities, and hence, stopping the computation process.

Fig.
2. The quantum-classical boundary. A classical computer can efficiently simulate
a system that behaves classically, but not one that behaves "quantumly." Hence
it is possible to identify a sharp transition between the quantum and classical
phases of some physical systems. For the first time, the physical form
of information has a qualitative rather than merely a quantitative bearing on
how efficiently the information can be processed, and the things that can be
done with it. (source, NSF)

As for communications,
quantum effects are similarly powerful and bizarre. There is quantum teleportation
(yep, its been proven to exist) which offers a convenient and safe way
to pass quantum information from one part of a quantum computer to another,
and even between quantum computers. A quantum computer can also be instantly
knowledgeable of anothers state (i.e., entangled), no matter how distant.
The usual laws of space and time seemingly do not apply in the quantum world.
The upshot is that if quantum information rather than classical information
is exchanged between systems, then the amount of communication required to perform
certain distributed tasks can be drastically reduced. All of these unique aspects
have obvious and major implications for the folks in the communications infrastructure
business.

The radical notion
of quantum computation has been around for some time. This wild idea first began
making the rounds in the 1970s and 1980s, promulgated by people
of the likes of Richard Feynman, Paul Benioff, David Deutsch, Charles Bennett,
and some other visionaries. But until the early 1990s it was mostly dismissed
as just another esoteric exercise for the theoretical physicists. However, the
role of quantum effects in silicon systems was well known and understood. Present-day
electronic devices rely on quantum mechanics. It is the wave nature of the electron
travelling through the periodic potential of the crystal that provides the starting
point for everything done in silicon systems (it produces the 1.1 eV stop band).
It wasn't until it was shown that quantum devices could do astonishing feats
with cryptographic algorithms that the finally field took off.

Peter Shor of
AT&Ts Bell Labs published a paper in 1994 that finally got peoples
quantum attention. His paper, "Algorithms for quantum computation: discrete
logarithms and factoring", gave the NSA and many commercial folks (banks,
etc.) who rely on ultrasecure crypto codes a very rude wake up call. Shor showed
in his paper how quantum computers could rapidly calculate the factors of very
large numbers. Such large numbers are at the core of modern cyrpto codes. Factoring
(calculating the divisors) of a 512-bit number, which is about 155 decimal digits,
and even that of much bigger numbers might turn out to be childs play
for a quantum computer.

Until Shors
paper arrived on the startled security scene, it had been safely assumed that
factoring extremely large primes, even on the biggest supercomputers, would
take billions of years. Some problems are tractable and others are intractable.
The latter become exponentially harder; i.e., they dont scale. A problem
of size N is said to be tractable if its solution takes a length of time that
depends on a polynomial function of N - that is, an algebraic power of
N such as N squared, N cubed, and so on. The computational resources required
for a tractable problem generally scale with the numbers in a moderate way.
If, on the other hand, the time taken to solve a problem blows up exponentially
with the size of the input  for example, on the order 2N or
greater -- the problem is deemed to be intractable. It just wont scale.
Factoring extremely large primes, e.g., code breaking, had been assumed to be
such an intractable problem.

But Shor shook
the safe house. He showed, to the shock of many, that by using quantum rules
there was a polynomial-time algorithm for factoring. Suddenly, the security
of nations and the global banking system was seen to possibly be at grave risk.
Its therefore no wonder that quantum information science was suddenly
catapulted from its lofty intellectual aerie down to brass tacks urgency. Since
Shors seminal 1994 paper, the field now known as quantum information science
has slowly but inexorably been making its way into a large number of back room
and not so back room projects in a wide variety of commercial, governmental,
and university settings.

For quantum computing
to succeed commercially and on a large scale, at least the following technology
areas will have to have been successfully tackled:

Error-correcting
systems for quantum computers and communications.

Techniques
for creating highly reliable quantum devices.

New classes
of quantum algorithms that significantly broaden the utility of these remarkable
devices.

New manufacturing
know how and materials technologies for building highly scalable, small sized,
and inexpensive quantum devices.

So
how do you maintain a coherent quantum computer system (all the atoms
or particles are in the same quantum state regardless of whether the state is
a superposition) and its crucial entanglement? You cant go anywhere near
it or observe it; in fact, a stray photon or a colliding atom will ruin the
computation completely or cause huge errors. And how do you "read out"
a definitive quantum answer without destructively interfering with the very
computation you went to such pains to set up? (Even spookier, it has been experimentally
shown that what you simply intend to measure is enough to determine the
quantum outcome! The quantum world is like a huge psychic massage parlor; you
think it and it will unkink it.)

At
first, the rules of classic Boolean logic dont seem to apply to quantum
information science. However, as noted, quantum computers are intrinsically
reversible, so you can take the AND of two bits and place them into a third
in an unobserved fashion. Moreover, so long as these bits are unobserved (not
interfered with), the bits can be in superposition of different values, as indeed
can the state of a whole register. This is a nonsense notion so long as you
think in terms of a macroscopic, i.e., classical computing, means of controlling
the register, like via a gate voltage. But once you dispense with such macroscopic
notions and do all the control at the atomic or microscopic level, reliable
quantum systems with programmable logic become a reality.

Some
of the first functioning quantum systems therefore rely on working completely
at the atomic level. One quantum computer contender is ion trap technology.
Trap approaches vary, but fundamentally the idea is to convince some ionized
atoms or other charged particles to get into an evacuated chamber, and then
hold them there using magnetic, static electric and/or radio frequency fields.
Ions are just atoms that have lost or gained one or more electrons, thus acquiring
an electrical charge. But even so trapped, the struggling atoms put up a thermal
ruckus that interferes in creating a coherent state useful for quantum computation.
To overcome the thermal fuss, special supercooling techniques using lasers have
been developed.

In
1994 (clearly, a seminal year in quantum computing science) two very clever
theoretical physicists, Ignazio Cirac and Peter Zeller at the University of
Innsbruck Austria, had the notion that the minimized vibrations of cooled, trapped
particles could be used to create a quantum computer. They subsequently showed
that with three precisely timed laser pulses the interacting vibrations between
qubits produced a controlled-NOT operation, which is also called an exclusive-OR
logic gate. (The state of one input controls whether the signal presented at
the other input is inverted at the output.) Moreover, as the effects rippled
right down the whole qubit chain, the qubits did not have to be adjacent to
each other to create this operation. They also showed that it was possible to
create three-bit gates or higher by directing additional laser pulses aimed
at other ions in this trapped string of atomic pearls. The coherence times lasted
about a thousandth of second. And so in 1995, one year after Cirac and Zellers
pivotal insight, the first-ever quantum logic gate arrived on the scene. Programmable
systems at the atomic level were now a reality.

Fig.
3. Andrew Steane and Derek Stacey of Oxford University have also developed a
quantum ion trap system. This is a picture of their ion trap electrode structure.
The trapping electrodes are the central ones, and are approximately 1 mm in
diameter. There are four long thin electrodes about 3 cm in length that provide
horizontal confinement, and two short pin-like electrodes at each end that provide
confinement along the axis. The rest of the structure consists of auxiliary
electrodes and steel rods to support everything. (source, Oxford University)

Fig.
4. Ions in Oxford: six calcium ions glowing in the center of their trap

But
like all quantum devices, ion trap-based systems have their drawbacks. The coherence
times need to be much improved (although Circa and Zeller have recently said
they can now achieve coherence times of about ten minutes). However, even these
two very ardent fans of ion trap systems admit that ion traps will probably
run out of scalability steam at about 2,000 qubits, if that number is truly
achievable at all.

Another
type of quantum computing system relies on Nuclear Magnetic Resonance (NMR),
which is more or less the same as Magnetic Resonance Imaging (MRI). The only
real distinction between MRI and NMR is the nomenclature (Dont want to
scare off those poor patients with the word "Nuclear", do we doctor?).
Hence, MRI is used on humans and NMR is used in chemistry and spectroscopy.
This exotic-sounding technique detects magnetic properties of nuclear spins
in both chemical and biological materials. For example, the single proton nucleus
of each hydrogen atom has a particular spin e.g. "up" or "down" (or a quantum
superposition of both up and down). When a material is immersed in a strong
static magnetic field and then exposed to a second dynamic field and/or electromagnetic
(e.g. RF) radiation, some proton spins are altered and eventually relax to their
original orientation (imagine a spinning top canting over from the vertical).
This precession of the nuclei about a magnetic field produces a very weak, but
highly characteristic, measurable signal. The medium and other conditions in
which the protons find themselves determine their response. If you are doing
a MRI, these atomic-level signals will produce a computer-enhanced image to
diagnose for injury or disease.

But
if you are doing NMR for quantum computing, you can achieve something else
entirely. By filling a test tube with a liquid comprised of appropriate molecules
(coffee does very nicely!) you can "program" the NMR system. Creating
logic gates is possible by using the interacting spins of two nuclei. By then
using precise radio frequency pulses as "software" you can alter
the interacting atomic spins in a highly particular way, e.g., your code-breaking/factoring
algorithm, so the nuclei will perform a useful calculation. Using NMR also
elegantly addresses the problem of decoherence -- The interfering phenomenon
that destroys the utility of a quantum system. Nuclear spins in a NMR quantum
computer can have long coherence times, lasting from many seconds to minutes
in liquids. And in gases, the times can last hours. Finally, you need to read
out the answer  the very weak but measurable signal produced by the
precession of the nuclei in the NMRs magnetic field.

But
you cant
measure the signal directly because that will interfere with the incredibly
delicate coherent state of the system and contaminate the answer with errors.
By using a huge number of individual quantum computers instead of just one
representing each qubit (the fundamental building block of a quantum computer)
you can afford to let your measurements interact with a few of them and still
get a reliable answer. This type of multi-qubit system is known as an ensemble
quantum computer (EQC) and its result measurement as ensemble averaging.
IBM,
The Institute of Theoretical Physics at Santa Barbara, Harvard Medical School,
the MIT Media Lab, and Oxford University, to name just some, have all built
functioning quantum computers based on NMR technology. There is also a formal
quantum NMR quantum collaboration project between researchers at Stanford
University, U.C. Berkeley, MIT, and IBM (see squint.stanford.edu).

Fig.
5 IBM physicists Isaac Chuang and Costantino Yannoni performing a NMR quantum-computing
experiment (the NMR device is the big cylinder in the background) at IBMs
Almaden research facilities. They announced their quantum computing success
at the 2000 Hot Chips conference. [IBM-Almaden photo]

One
catch (and there are others) to the NMR approach is that your average cup
of Starbucks has more than a hundred billion trillion molecules all charging
off into different caffeine crazed directions. If the quantum-computing goal
is to start off with a coherent system that you can reliably and consistently
set up and use, this is not good. You could possibly isolate and trap some
of these bouncing molecules and get them into a coherent state by using something
called an atomic force microscope (AFM) and set them up the way you want.
Unlike traditional microscopes, scanned-probe AFM systems do not use lenses,
so the size of the probe rather than diffraction effects generally limit their
resolution. AFMs can achieve a resolution of 10 pm, and also unlike electron
microscopes, can work on samples in air and under liquids, like that coffee-filled
quantum system. But using AFMs in quantum systems is still an ongoing area
of exploration. As an alternative to using an AFM, you could rely on the fact
that most of the NMR signals average out to zero. You could then scheme up
ways to get just a few desired molecules to stand out from the silent crowd
and use these highly vocal lads as your qubits. Several techniques have been
shown to be effective in orchestrating such a quantum computing chorus call.

Fig.
6. A "desktop quantum computer." This machine consists of two magnets with
a space between them for the tube with a liquid (coffee works quite nicely)
made up of appropriate molecules. Inexpensive table-top devices now under
development, like the one sketched here, will be able to outperform the costly
commercial NMR spectrometers that are used in current studies of room temperature
ensemble quantum computation. (source, NSF)

Neil Gershenfeld
of MITs Media Lab has said that Round about fifty qubits is when
you begin to beat classical computers." But easily achieving that fifty+
qubit number in a NMR system appears to be remote and there is currently a
hot debate about whether NMR-based quantum systems will ever be more than
first step technical curiosities, despite their early promise.

Another approach
to constructing quantum devices builds on the 1960s discovery of molecular
beam epitaxy (MBE) at Bell Labs. In MBE, the constituent elements of a semiconductor
in the form of molecular beams are deposited onto a heated crystalline
substrate to form thin epitaxial layers. Basically, MBE is used to vaporize
materials like aluminum and gallium arsenide in separate chambers. These vaporized
materials are then joined together layer by atomic layer in another chamber
by carefully spraying them on a wafers surface. Growth rates are typically
on the order of a few Å/s and the beams can be shuttered in a fraction
of a second, allowing for nearly atomically abrupt transitions from one material
to another. The technique is so precise that these different layers form a
single crystal with their respective lattices precisely lining up top to bottom.
It is the resulting precise atomic structure lattice that holds the quantum-computing
key. If the electrons dont scatter as they move through the layers,
as they do in conventional semiconductors, they can achieve coherence, the
essential ingredient for a quantum computing system.

Whats
especially appealing about MBE is that it can be used to create large numbers
of self-assembling quantum dots -- miniscule semiconductors on a chip surrounded
by an insulator such as aluminum gallium arsenide.

Fig.
7. Schematic of a quantum dot (Source, MITRE)

Single
electrons are readily observable in a quantum dot, via a voltage jump, as
they move in and out of these islands that are just a few hundred atoms across.
Obviously, if quantum dot technology is commercially perfected (the major
semi-memory makers in Japan take quantum dot technology very seriously), memory
capacity of these microdevices will be extraordinary.

However,
as far back 1994, researchers and theoreticians such as Adriano Barenco, David
Deutsch and Artur Ekert postulated that quantum dots could also be used to
implement conditional quantum logic. Barenco, who is at Oxford University
in the UK, showed that the state of one quantum dot could be used to alter
the behavior of another, leading to the possibility of creating programmable
logic gates and low cost, easy to make quantum computers. (Oxford is the site
of some of the most important and exciting research in the quantum field.)
Sandia National Labs has also recently uncovered a repulsion effect between
quantum dots, and this effect may completely govern the way they organize
themselves.

But
quantum dots have their own problems when it comes to quantum computation.
Unlike NMR-based systems whose nuclear spins for a quantum computation have
very long coherence times ranging from seconds to hours, quantum dots are
notoriously reluctant to maintain appreciable coherence. Typically, coherence
lasts about a billionth of a second. The primary culprits are thermal vibration
and material impurities. The quantum house of computational cards collapses
in a nanosecond.

But
interestingly, Josephson junctions, the great superconducting hope for building
wicked fast, but very low energy supercomputers that first surfaced in the
1970s and which then just as quickly faded from view, seem to be on
the comeback trail. A Josephson junction is a weak link between two superconducting
films separated by a thin oxide layer enabling the tunneling of Cooper pairs
of electrons. Josephson junctions may solve the coherence stability dilemma
that to date has plagued quantum dot systems designers. There have been some
recent quantum success stories using these superconducting devices. For example
Nakamura, Pashkin and Tsai of NEC Fundamental Research Laboratories in Tsukuba,
Japan demonstrated a Josephson junction quantum computer in April 1999. Although
the NEC researchers did not perform any quantum calculations with their achievement,
it was a notable breakthrough and there are growing indications that Josephson
junctions might play a major role in building quantum computers. For example,
D.V. Averin (Department of Physics and Astronomy, SUNY at Stony Brook) will
be giving a paper in March 2001 at an American Physical Society meeting that
discusses a recent experimental demonstration of a single qubit operation
using a superconducting Josephson junction.

Scalability,
error correcting, and coherence are the trinity that makes up the Holy Grail
of the quantum quest. Quantum dots probably hold the greatest promise of becoming
the most scalable of all current quantum design ideas. Numbers in excess of
1,000+ qubits are being thrown about for fully realized quantum dot systems,
and much greater qubit densities will likely be possible as manufacturing
techniques gain in sophistication. This is way ahead of NMR systems, which
seem to be struggling with achieving qubit numbers of even fifty or so. Meanwhile,
it seems that Ion traps may top out at about 2,000 qubits, and even that sounds
quite optimistic.

Apparently,
driving this scalability mania (and also a good deal of the fields funding)
are the good people at the NSA and other deep spook agencies around the world.
The factorization-cyrpto breakers seem to want to have at least a few thousand
qubits to do meaningful work. To put that numerical goal in perspective, bear
in mind that a quantum computers power increases exponentially. In general,
L qubits can store 2L numbers at once. Thus, three qubits can store
8 different numbers at once, four qubits can store 16 numbers at once, and
on up it goes. Now imagine the computing power in a system having several
thousand qubits!

But quantum
computer acting on even just hundreds of qubits is capable in principle of
performing tasks that could never be performed by conventional digital computers.
For example, a classical computer requires a time proportional to N
to search for a particular item in a list of N items,
whereas a quantum computer can perform the search in a time proportional to
the square root of N.

Even with several
K qubits pumping exponentially away in a system that stays coherent for hours
on end, you still have the problem of error correction. A quantum computer
is the quintessential black go-boom box. Any type of disturbing, i.e., interfering
behavior, will cause the incredibly fragile contraption to stop working in
a snit of decoherent quantum mechanics pique. So how do you know or ensure
that the qubit results you have been able to ever so slyly pull out are correct?
Once again, it was left to Peter Shor of ATT Bell labs to set the quantum
world on its ear. In 1995 he announced his discovery of an algorithm that
achieved reliable quantum error correcting.

Fundamentally,
Shors new algorithm took advantage of the fact that it only dealt with
the "noise" inherent in the quantum system and completely disregarded
the signal, or information. By subtracting out the noise, you are left with
a reliable result. His algorithm proved that it was possible to restore the
quantum state to its original form without any contaminating errors creeping
in. Moreover, to almost everyones surprise and research delight, he
showed that you could pull off this rabbit in a quantum hat trick by correcting
individual qubits. Up until Shor showed otherwise, it had been assumed that
measuring such individual qubit operations would contaminate and crash the
entire system.

Almost immediately
after Shors breakthrough was announced, it was found that Andrew Steane
of Oxford had independently discovered another error correction scheme. Since
1995, a slew of ever-refined quantum error correcting methodologies has been
discovered, most of which build on Shor and Steanes original insights.

Fig.
8. The secret of quantum error correction is to encode a quantum state in
a cleverly selected subspace of a larger vector space. Errors that move the
vector in a direction perpendicular to the code subspace can easily be detected
and reversed, while errors parallel to the code subspace cause trouble. But
if the code subspace is carefully chosen, typical errors will have only a
very small component along the code subspace, and encoded information will
be well protected.Entanglement is an essential feature of quantum
error-correcting codes. (source, NSF)

It is now 2001,
and we have more than six years experience in designing, building and operating
quantum computers, of many different stripes. And almost certainly, better
materials and technologies than NMR, quantum dots, and ion traps will soon
be appearing, for such is the nature of scientific discovery these days. So
what will you do when this wonderfully weird thing finally lands in your palm?
Cracking crypto codes may be a good time for some, but thats still a
pretty limited (if potentially immensely rewarding) field of activity. Current
wisdom has it that algorithms that work in an iterative fashion with many
intermediary steps, for example weather forecasting, will not be the province
of quantum computers and we will still need conventional, "classic"
systems to do that kind of algorithmic work.

But maybe not,
as apparently human beings routinely use quantum computing to perform the
widest imaginable variety of tasks. It seems your brain is also a quantum
computer! For example, a new method for doing a MRI of the brain is based
on the detection of quantum coherence. The new MRI technique was recently
developed at Princeton University, University of Pennsylvania, and the University
of Minnesota. The methods, intermolecular multiple quantum coherence "IMQC"
and intermolecular zero quantum coherence "IZQC", were created to enhance
the contrast of a conventional MRI and offer much greater resolution. The
MRI magnet and excitation techniques externally induce quantum coherence in
the brain. Quantum dipole couplings of proton spins in two molecules (e.g.
water, protein) separated by distances ranging from 10 microns to one millimeter
yield detectable MRI signals under certain conditions. While it is true this
coherence is an artifact produced from outside the brain by the MRI system,
that your wet and noisy brain can support detectable quantum coherence of
any kind comes as a shock to most people, including many well-established
researchers. It also supports the growing idea that our brain may be quite capable
of naturally producing quantum coherence.

This scientific evidence could indicate that coherent quantum processing is naturally occurring
all the time in the brain. And so, incredibly, the key to unlocking the secrets of reliable
quantum computing -- and keeping the lights on -- may have been not under,
but on top of our noses all along.